Determining and displaying reserve estimates for a reservoir

ABSTRACT

Systems and methods for determining and displaying reserve estimates for a reservoir by generating a table and, optionally, a report and/or a graph for the reserve estimates and predefined identification properties that uniquely describe the reserve estimates.

CROSS-REFERENCE TO RELATED APPLICATIONS

This Application claims priority from PCT Patent Application Serial No.PCT/US14/51326, filed on Aug. 15, 2014 which claims priority from U.S.Provisional Patent Application Ser. No. 61/866,901, filed on Aug. 16,2013, which are incorporated herein by reference.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH

Not applicable.

FIELD OF THE DISCLOSURE

The present disclosure generally relates to systems and method fordetermining and displaying reserve estimates for a reservoir. Moreparticularly, the present disclosure relates to determining anddisplaying reserve estimates for a reservoir by generating a table and,optionally, a report and/or a graph for the reserve estimates andpredefined identification properties that uniquely describe the reserveestimates.

BACKGROUND

Accurate reserve estimates are critical in the industry for proper riskassessment and providing these in a structural framework setting isunique. Traditional volumetric calculations are purely grid-based anddefine the volume between surfaces/horizons by computing and summarizinghorizontal slices. The slicing technique does not accurately definegeologic volumes especially with complex geometries such as fault blocksor salt bodies. In addition, it is challenging for the user to gain anaccurate three-dimensional visual representation of the calculatedvolumes. Geocellular-based volume calculations also inadequately definevolumes due to stair-stepped geometry representations.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is described below with references to theaccompanying drawings in which like elements are referenced with likereference numerals, and in which:

FIG. 1 is a flow diagram illustrating one embodiment of a method 100 forimplementing the present disclosure.

FIG. 2 is a flow diagram illustrating one embodiment of a method 200 forimplementing step 106 in FIG. 1.

FIG. 3 is a flow diagram illustrating one embodiment of a method 300 forimplementing step 110 in FIG. 1.

FIG. 4 is a flow diagram illustrating one embodiment of a method 400 forimplementing step 112 in FIG. 1.

FIG. 5 is a flow diagram illustrating one embodiment of a method 500 forimplementing step 114 in FIG. 1.

FIG. 6 is a flow diagram illustrating one embodiment of a method 600 forimplementing step 120 in FIG. 1.

FIG. 7 is a display illustrating exemplary predefined identificationproperties linked to a sealed triangulated mesh that is displayed atfour different time intervals using the printable string stored in step508 of FIG. 5 and a 3D modeling engine.

FIG. 8 is a display illustrating an exemplary tree table created in step604 of FIG. 6.

FIG. 9 is a display illustrating an exemplary HTML report created with adefault XSL in step 614 of FIG. 6.

FIG. 10 is a block diagram illustrating one embodiment of a computersystem for implementing the present disclosure.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The present disclosure overcomes one or more deficiencies in the priorart by providing systems and methods for determining and displayingreserve estimates for a reservoir by generating a table and, optionally,a report and/or a graph for the reserve estimates and predefinedidentification properties that uniquely describe the reserve estimates.

In one embodiment, the present disclosure includes a method fordetermining reserve estimates for a reservoir, which comprises: i)loading a sealed triangulated mesh, which includes a volume; ii)creating a thickness grid using the sealed triangulated mesh and acomputer processor; iii) determining reserve estimates in a reservoirmodel using one of the volume of the sealed triangulated mesh and thethickness grid; iv) converting the reserve estimates, the sealedtriangulated mesh and the thickness grid into a printable string; v)storing the printable string in Processing History fields with a link toa 3D modeling engine and predefined identification properties describingthe reserve estimates; and vi) generating at least one of a table, areport and a graph for the reserve estimates and the predefinedidentification properties using the printable string.

In another embodiment the present disclosure includes a non-transitoryprogram carrier device tangibly carrying computer-executableinstructions for determining reserve estimates for a reservoir, theinstructions being executable to implement: i) loading a sealedtriangulated mesh, which includes a volume; ii) creating a thicknessgrid using the sealed triangulated mesh; iii) determining reserveestimates in a reservoir model using one of the volume of the sealedtriangulated mesh and the thickness grid; iv) converting the reserveestimates, the sealed triangulated mesh and the thickness grid into aprintable string; v) storing the printable string in Processing Historyfields with a link to a 3D modeling engine and predefined identificationproperties describing the reserve estimates; and vi) generating at leastone of a table, a report and a graph for the reserve estimates and thepredefined identification properties using the printable string.

In yet another embodiment, the present disclosure includes anon-transitory program carrier device tangibly carryingcomputer-executable instructions for determining reserve estimates for areservoir, the instructions being executable to implement: i) loading asealed triangulated mesh, which includes a volume; ii) creating athickness grid using the sealed triangulated mesh; iii) determiningreserve estimates in a reservoir model using one of the volume of thesealed triangulated mesh and the thickness grid; iv) converting thereserve estimates, the sealed triangulated mesh and the thickness gridinto a printable string; v) storing the printable string with a link toa 3D modeling engine and predefined identification properties describingthe reserve estimates; vi) generating at least one of a table, a reportand a graph for the reserve estimates and the predefined identificationproperties using the printable string; and vii) displaying the sealedtriangulated mesh and the thickness grid with the at least one of thetable, the report and the graph.

The subject matter of the present disclosure is described withspecificity; however, the description itself is not intended to limitthe scope of the disclosure. The subject matter thus, might also beembodied in other ways, to include different steps or combinations ofsteps similar to the ones described herein, in conjunction with otherpresent or future technologies. Moreover, although the term “step” maybe used herein to describe different elements of methods employed, theterm should not be interpreted as implying any particular order among orbetween various steps herein disclosed unless otherwise expresslylimited by the description to a particular order. While the presentdisclosure may be applied in the oil and gas industry, it is not limitedthereto and may also be applied in other industries to achieve similarresults.

Method Description

The present disclosure describes various approaches for computing grossrock volumes (GRV) and reserves while running multiple scenarios,keeping track of the calculation history and even restoring formervolumes visually for time-lapse analyses. The present disclosure furtheroffers a unique workflow for performing highly accurate GRV and reservecalculations in a dynamic structural framework setting.

This disclosure complements a new direction in 3D modeling where sealedtriangulated mesh spaces, also referred to as called compartments, aremodeled instead of just the geological objects (e.g. surfaces, faults,geoshells, fluid contacts). These compartments are auto-grouped intodifferent geologic categories such as stratigraphic layers, faultblocks, fluid layers and geoshells, or they may be grouped manually intocustom reservoirs, to help identify the exact GRV and/or reservecalculations. The modeled volumes may be visualized in all views bycolor and/or lithology fills.

This disclosure thus, provides a number of techniques that work bycombining closed triangulated mesh compartments. The volumes of all theindividual triangulated mesh bodies comprising compartments are obtainedthrough a direct polyhedral volume calculation and are added together toproduce a GRV for the interior space of each compartment. This value canthen be used in numerical reserve estimates or in a new feature thatuses extracted thickness values to perform grid-based reserve estimates.

At all stages of the analysis, the actual sealed space being analyzed isvisible. A subset of the sealed model is isolated and preserved for bothanalysis and later viewing, making it easy to visualize what wascomputed and how it changes through time. All thickness and reservecalculations can also be viewed as 3D grids and used to generate varyingscenarios both visually and numerically at any stage in the reserveestimation process.

Referring now to FIG. 1, a flow diagram of one embodiment of a method100 for implementing the present disclosure is illustrated.

In step 102, the method 100 determines if a new scenario should becreated using the client interface and/or the video interface describedin reference to FIG. 10. If a new scenario should not be created, thenthe method 100 proceeds to step 116. Otherwise, the method 100 proceedsto step 104.

In step 104, a sealed triangulated mesh is loaded. The sealedtriangulated mesh includes a volume that is computed in the unit systemof any well-known 3D modeling engine using techniques well known in theart such as Stoke's Theorem.

In step 106, fast sweep thickness extraction is performed on the sealedtriangulated mesh from step 104 to create a thickness grid. Oneembodiment of a method for performing this step is described further inreference to FIG. 2.

In step 108, the method 100 determines if reserve estimates should becomputed with only numeric values using the client interface and/or thevideo interface described in reference to FIG. 10. If reservecalculations should not be computed with only numeric values, then themethod 100 proceeds to step 112. Otherwise, the method 100 proceeds tostep 110.

In step 110, numeric reserve estimates are computed using the volume forthe sealed triangulated mesh loaded in step 104 and the method 100proceeds to step 114. One embodiment of a method for performing thisstep is described further in reference to FIG. 3.

In step 112, spatially aware reserve estimates are computed using thethickness grid from step 106. One embodiment of a method for performingthis step is described further in reference to FIG. 4.

In step 114, a persistence and restored state are maintained for thereserve estimates computed in step 110 or step 112 by storing them withthe sealed triangulated mesh loaded in step 104 and the thickness gridfrom step 106 as a printable string in one or more Processing Historyfields. One embodiment of a method for performing this step is describedfurther in reference to FIG. 5.

In step 116, the method 100 determines if there are any reserveestimates stored in one or more of the Processing History fields fromstep 114. If there are no reserve estimates stored in the one or moreProcessing History fields, then the method 100 ends. Otherwise, themethod 100 proceeds to step 118.

In step 118, the reserve estimates and linked predefined identificationproperties from step 114 are loaded from the one or more ProcessingHistory fields.

In step 120, a table and, optionally, a report and/or a graph aregenerated for the reserve estimates and predefined identificationproperties loaded in step 118. One embodiment of a method for performingthis step is described further in reference to FIG. 6.

Fast Sweep Thickness Extraction

Referring now to FIG. 2, a flow diagram illustrating one embodiment of amethod 200 for implementing step 106 in FIG. 1 is illustrated. Themethod 200 performs a fast sweep thickness extraction on the sealedtriangulated mesh from step 104 to create a thickness grid. Thethickness grid may be multiplied by a constant value or by one or moreother grids with laterally-varying attributes to produce reserveestimates.

In step 202, the sealed triangulated mesh from step 104 is loaded.

In step 204, a predefined slice interval and a predefined thicknessinterval are loaded.

In step 206, a plurality of polylines is created by intersecting avertical plane with the sealed triangulated mesh from step 202 at thepredefined slice interval from step 204 along an x-dimension in spatialextents for the sealed triangulated mesh using contouring techniquesthat are well known in the art. Each polyline includes a first point anda last point.

In step 208, a plurality of polygons is created by connecting the firstpoint and the last point of each polyline in a respective verticalplane. Each polygon in the plurality of polygons lies in a respectivevertical plane defined by the intersection of the vertical plane withthe sealed triangulated mesh at the predefined slice interval.

In step 210, each polygon in the plurality of polygons from step 208 isaligned perpendicular to the respective vertical plane.

In step 212, a grid is created having an equal number of rows andcolumns, spatial extents that match the spatial extents of the sealedtriangulated mesh from step 202, a grid x-dimension cell size equal tothe predefined slice interval from step 204 and a grid y-dimension cellsize equal to the predefined thickness interval from step 204. Each gridnode is initialized with a value of zero. The grid, for example, mayhave 1000 rows and 1000 columns for computing efficiency and broadapplication coverage. The grid is preferably positioned above the sealedtriangulate mesh from step 202.

In step 214, a plurality of thickness values are computed usingtechniques well-known in the art and each aligned polygon at thepredefined thickness interval from step 204.

In step 216, a thickness grid is created by assigning each thicknessvalue in the plurality of thickness values computed in step 214 to arespective grid node on the grid created in step 212 using thepredefined slice interval from step 204 and the predefined thicknessinterval from step 204. The predefined slice interval and the predefinedthickness interval are used to assign each thickness value to arespective grid node by assigning each thickness value corresponding toa respective vertical plane at the predefined slice interval andpredefined thickness interval to a respective grid node on the grid atan x-dimension corresponding to the respective vertical plane at thepredefined slice interval and at a y-dimension corresponding to thepredefined thickness interval. The thickness grid is returned to step106 in FIG. 1.

Numeric Reserve Estimates

Referring now to FIG. 3, a flow diagram of one embodiment of a method300 for implementing step 110 in FIG. 1 is illustrated. The method 300computes numeric reserve estimates using the volume for the sealedtriangulated mesh loaded in step 104.

In step 302, the volume for the sealed triangulated mesh from step 104is loaded.

In step 304, Original Oil In Place (OOIP) is calculated by multiplyingthe volume loaded in step 302 and a predefined percent value for Net toGross Ratio (NTG Ratio), porosity, and hydrocarbon saturation.

In step 306, Stock Tank Original Oil In Place (STOOIP) is calculated bydividing the OOIP calculated in step 304 by a predefined FormationVolume Factor (FVF).

In step 308, Recoverable Hydrocarbon Reserves (RHCR) is calculated bymultiplying the STOOIP calculated in step 306 and a predefined recoveryfactor. The numeric reserve estimates (RHCR) are returned to step 110 inFIG. 1.

Spatially Aware Reserve Estimates

Referring now to FIG. 4, a flow diagram of one embodiment of a method400 for implementing step 112 in FIG. 1 is illustrated. The method 400computes spatially aware reserve estimates using the thickness grid fromstep 106. A defining feature of the method 400 is the ability to matchthe thickness grid and an attribute grid. The thickness grid representsthe aggregate vertical thickness of a compartment at each grid node. Themethod 400 enables the thickness grid to be multiplied by one or moregrids of laterally-varying attributes to produce a unified grid. Grossvolumes may then be derived from gross thickness grids and net volumesmay be acquired from the unified grids.

In step 402, an attribute grid, a constant value, a predefined FVF, anda predefined recovery factor are loaded. The attribute grid includes anattribute grid node at each intersection of the attribute gridrepresenting a plurality of attribute grid nodes, wherein each attributegrid node has an attribute value. The attribute grid thus, may representattributes such as porosity or permeability, for example.

In step 404, the attribute grid from step 402 is resampled usingresampling techniques well known in the art such as bicubicinterpolation to match the attribute grid and the thickness grid fromstep 106 so that the attribute grid includes an attribute grid node ateach location of a thickness grid node. As a result, some of theattribute grid nodes may have an attribute value that is null when theattribute grid and the thickness grid are not the same size.

In step 406, a unified grid is created by multiplying the thicknessvalue of each grid node on the thickness grid from step 106 and theattribute value of each respective resampled attribute grid node fromstep 404. The unified grid thus, includes a unified grid node at eachlocation of an attribute grid node representing a plurality of unifiedgrid nodes, wherein each unified grid node has a value that is theproduct of the thickness value of a thickness grid node at the samelocation and the attribute value of a respective resampled attributegrid node at the same location. The value of a unified grid node isinvalid if the thickness value of a thickness grid node is at the samelocation is multiplied by a null attribute value of a respectiveresampled attribute grid node at the same location. The unified gridalso defines a plurality of cells, wherein each cell includes four sidesand a center.

In step 408, the method 400 determines if the value of each unified gridnode is valid. If the value of each unified grid node is valid, then themethod proceeds to step 418. Otherwise, the method proceeds to step 410.

In step 410, the method 400 determines whether to replace each invalidvalue for a respective unified grid node with the constant value fromstep 402 using the client interface and/or the video interface describedin reference to FIG. 10. If each invalid value for a respective unifiedgrid node should not be replaced with the constant value, then themethod 400 proceeds to step 414. Otherwise, then the method 400 proceedsto step 412.

In step 412, the unified grid created in step 406 is converted to anOOIP grid by replacing each invalid value for a respective unified gridnode with the constant value from step 402. The OOIP grid thus, includesan OOIP grid node at each location of a respective unified grid noderepresenting a plurality of OOIP grid nodes, wherein each OOIP grid nodehas a value that is the same value as the valid value of the respectiveunified grid node or the constant value. The OOIP grid defines aplurality of cells, wherein each cell includes four sides and a center.The method 400 then proceeds to step 418.

In step 414, an average value for each unified grid node with an invalidvalue is calculated by dividing the sum of the attribute values for theresampled attribute grid nodes from step 404 by the total number ofresampled attribute grid nodes from step 404.

In step 416, the unified grid created in step 406 is converted to anOOIP grid by replacing each invalid value for a respective unified gridnode with the average value calculated in step 414. The OOIP grid thus,includes an OOIP grid node at each location of a respective unified gridnode representing a plurality of OOIP grid nodes, wherein each OOIP gridnode has a value that is the same value as the valid value of therespective unified grid node or the average value. The OOIP grid definesa plurality of cells, wherein each cell includes four sides and acenter.

In step 418, each cell of the unified grid from step 406, or each cellof the OOIP grid from step 412 or step 416, is divided into fourtriangles. Each of the four triangles for each cell includes a vertex atthe center of the respective cell and two vertices that form one of thefour sides of the respective cell. Each vertex includes an x, y, zvalue.

In step 420, a truncated prism having a volume is created for each setof four triangles from step 418 by connecting each vertex for arespective triangle to a plane including only the x value and the yvalue of the respective vertex at z=0.

In step 422, OOIP is calculated as the sum of the volumes of thetruncated prisms created in step 420.

In step 424, STOOIP is calculated by dividing the OOIP calculated instep 422 by the FVF from step 402.

In step 428, RHCR is calculated by multiplying the STOOIP calculated instep 424 by the recovery factor from step 402. The spatially awarereserve estimates (RHCR) are returned to step 112 in FIG. 1.

Persistence and Restored State

Referring now to FIG. 5, a flow diagram of one embodiment of a method500 for implementing step 114 in FIG. 1 is illustrated. The method 500maintains persistence and restored state for the reserve estimatescomputed in step 110 or step 112 by storing them with the sealedtriangulated mesh loaded in step 104 and the thickness grid from step106 as a printable string in one or more Processing History fields. Inthis manner, the reserve estimates are permanently saved withidentification, interpreter, date and parameters used. Each saved resultof any reserve estimate is linked to relevant predefined identificationproperties By saving the sealed triangulated mesh, thickness grid andreserve estimates in the Processing History fields, the structure can berecovered, visualized again, and used as a basis for additional analysiseven as the structure changes over time.

In step 502, the sealed triangulated mesh from step 104, the thicknessgrid from step 106 and the reserve estimates computed in step 110 orstep 112 are serialized into a byte array using techniques well known inthe art.

In step 504, the serialized byte array from step 502 is compressed usingtechniques well known in the art.

In step 506, the compressed byte array from step 504 is converted into aprintable string using UTF-8/ ASCII characters to make it compatiblewith standard Processing History fields.

In step 508, the printable string from step 506 is stored in one or moreof the Processing History fields with a link to the 3D modeling engineand relevant predefined identification properties that uniquely describethe reserve estimates represented by the printable string. The printablestring and predefined identification properties are returned to step 114in FIG. 1. In FIG. 7, a display 700 illustrates exemplary predefinedidentification properties linked to a sealed triangulated mesh 702, 704,706, 708 that is displayed at four different time intervals using the 3Dmodeling engine. In this manner, the reservoir model at a predeterminedtime may be dynamically compared to the reservoir model at anotherpredetermined time to improve the reserve estimates in the reservoirmodel.

Display and Reporting

Referring now to FIG. 6, a flow diagram of one embodiment of a method600 for implementing step 120 in FIG. 1 is illustrated. The method 600generates a table and, optionally, a report and/or a graph for thereserve estimates and the predefined identification properties loaded instep 118. The report provides abstracted control over the layout and thepossibility for additional custom defined layouts in the future.

In step 602, the sealed triangulated mesh from step 104, the reserveestimates and the predefined identification properties from step 118 areloaded.

In step 604, a tree table is created by linking the sealed triangulatedmesh and each respective reserve estimate using the predefinedidentification properties. In FIG. 8, a display 800 illustrates anexemplary tree table wherein each reserve estimate is represented by thevolume/units columns and includes the type of calculation, its date andthe interpreter.

In step 606, the method 600 determines if an advanced report should becreated using the client interface and/or the video interface describedin reference to FIG. 10. If an advanced report should not be created,then the method 600 proceeds to step 616. Otherwise, the method proceedsto step 608.

In step 608, the method 600 determines if there is a predefinedextensible style-sheet language (XSL) using the client interface and/orthe video interface described in reference to FIG. 10. If there is not apredefined XSL, then the method 600 proceeds to step 612. Otherwise, themethod 600 proceeds to step 610.

In step 610, the predefined XSL is loaded and interpreted and the method600 then proceeds to step 614.

In step 612, a default XSL is loaded and interpreted.

In step 614, a hyper-text markup language (HTML) report is created byprocessing the tree table from step 604 with the XSL loaded in step 610or step 612. In FIG. 9, a display 900 illustrates an exemplary HTMLreport created with the default XSL from step 612 wherein the individualparameters of each reserve estimate are shown such as the calculationname values for each parameter distinguished by each column.

In step 616, the method 600 determines if there are predefinedparameters for a graph using the client interface and/or the videointerface described in reference to FIG. 10. If there are no predefinedparameters for a graph, then the method 600 returns the table and, ifavailable, the report to step 120 in FIG. 1. Otherwise, the methodproceeds to step 618.

In step 618, a graph is formatted using predefined parameters and thetree table from step 604. The table and, if available, the report and/orthe graph are returned to step 120 in FIG. 1.

System Description

The present disclosure may be implemented through a computer-executableprogram of instructions, such as program modules, generally referred toas software applications or application programs executed by a computer.The software may include, for example, routines, programs, objects,components and data structures that perform particular tasks orimplement particular abstract data types. The software forms aninterface to allow a computer to react according to a source of input.DecisionSpace© Geosciences, which is a commercial software applicationmarketed by Landmark Graphics Corporation, may be used as an interfaceapplication to implement the present disclosure. The software may alsocooperate with other code segments to initiate a variety of tasks inresponse to data received in conjunction with the source of the receiveddata. The software may be stored and/or carried on any variety of memorysuch as CD-ROM, magnetic disk, bubble memory and semiconductor memory(e.g., various types of RAM or ROM). Furthermore, the software and itsresults may be transmitted over a variety of carrier media such asoptical fiber, metallic wire and/or through any of a variety ofnetworks, such as the Internet.

Moreover, those skilled in the art will appreciate that the disclosuremay be practiced with a variety of computer-system configurations,including hand-held devices, multiprocessor systems,microprocessor-based or programmable-consumer electronics,minicomputers, mainframe computers, and the like. Any number ofcomputer-systems and computer networks are acceptable for use with thepresent disclosure. The disclosure may be practiced indistributed-computing environments where tasks are performed byremote-processing devices that are linked through a communicationsnetwork. In a distributed-computing environment, program modules may belocated in both local and remote computer-storage media including memorystorage devices. The present disclosure may therefore, be implemented inconnection with various hardware, software or a combination thereof, ina computer system or other processing system.

Referring now to FIG. 10, a block diagram illustrates one embodiment ofa system for implementing the present disclosure on a computer. Thesystem includes a computing unit, sometimes referred to as a computingsystem, which contains memory, application programs, a client interface,a video interface, and a processing unit. The computing unit is only oneexample of a suitable computing environment and is not intended tosuggest any limitation as to the scope of use or functionality of thedisclosure.

The memory primarily stores the application programs, which may also bedescribed as program modules containing computer-executableinstructions, executed by the computing unit for implementing thepresent disclosure described herein and illustrated in FIGS. 1-9. Thememory therefore, includes a visual volumetrics module, which enablessteps 106, 110, 112 and 120 described in reference to FIG. 1. The visualvolumetrics module may integrate functionality from the remainingapplication programs illustrated in FIG, 10. In particular,DecisionSpace® Geosciences may be used as an interface application toperform steps 102, 108, 116 in FIG. 1 while steps 104 and 118 may beperformed using the database. Although DecisionSpace® Geosciences may beused as an interface application, other interface applications may beused, instead, or the visual volumetrics module may be used as astand-alone application.

Although the computing unit is shown as having a generalized memory, thecomputing unit typically includes a variety of computer readable media.By way of example, and not limitation, computer readable media maycomprise computer storage media and communication media. The computingsystem memory may include computer storage media in the form of volatileand/or nonvolatile memory such as a read only memory (ROM) and randomaccess memory (RAM). A basic input/output system (BIOS), containing thebasic routines that help to transfer information between elements withinthe computing unit, such as during start-up, is typically stored in ROM.The RAM typically contains data and/or program modules that areimmediately accessible to, and/or presently being operated on, theprocessing unit. By way of example, and not limitation, the computingunit includes an operating system, application programs, other programmodules, and program data.

The components shown in the memory may also be included in otherremovable/nonremovable, volatile/nonvolatile computer storage media orthey may be implemented in the computing unit through an applicationprogram interface (“API”) or cloud computing, which may reside on aseparate computing unit connected through a computer system or network.For example only, a hard disk drive may read from or write tononremovable, nonvolatile magnetic media, a magnetic disk drive may readfrom or write to a removable, nonvolatile magnetic disk, and an opticaldisk drive may read from or write to a removable, nonvolatile opticaldisk such as a CD ROM or other optical media. Otherremovable/non-removable, volatile/nonvolatile computer storage mediathat can be used in the exemplary operating environment may include, butare not limited to, magnetic tape cassettes, flash memory cards, digitalversatile disks, digital video tape, solid state RAM, solid state ROM,and the like. The drives and their associated computer storage mediadiscussed above provide storage of computer readable instructions, datastructures, program modules and other data for the computing unit.

A client may enter commands and information into the computing unitthrough the client interface, which may be input devices such as akeyboard and pointing device, commonly referred to as a mouse, trackballor touch pad. Input devices may include a microphone, joystick,satellite dish, scanner, or the like. These and other input devices areoften connected to the processing unit through the client interface thatis coupled to a system bus, but may be connected by other interface andbus structures, such as a parallel port or a universal serial bus (USB).

A monitor or other type of display device may be connected to the systembus via an interface, such as a video interface. A graphical userinterface (“GUI”) may also be used with the video interface to receiveinstructions from the client interface and transmit instructions to theprocessing unit. In addition to the monitor, computers may also includeother peripheral output devices such as speakers and printer, which maybe connected through an output peripheral interface.

Although many other internal components of the computing unit are notshown, those of ordinary skill in the art will appreciate that suchcomponents and their interconnection are well known.

While the present disclosure has been described in connection withpresently preferred embodiments, it will be understood by those skilledin the art that it is not intended to limit the disclosure to thoseembodiments. It is therefore, contemplated that various alternativeembodiments and modifications may be made to the disclosed embodimentswithout departing from the spirit and scope of the disclosure defined bythe appended claims and equivalents thereof.

The invention claimed is:
 1. A method for determining reserve estimatesfor a reservoir, which comprises: loading a sealed triangulated mesh,which includes a volume; creating a thickness grid using the sealedtriangulated mesh and a computer processor; determining reserveestimates in a reservoir model using one of the volume of the sealedtriangulated mesh and the thickness grid; converting the reserveestimates, the sealed triangulated mesh and the thickness grid into aprintable string; storing the printable string in Processing Historyfields with a link to a 3D modeling engine and predefined identificationproperties describing the reserve estimates; and generating at least oneof a table, a report and a graph for the reserve estimates and thepredefined identification properties using the printable string.
 2. Themethod of claim 1, further comprising displaying the sealed triangulatedmesh and the thickness grid with the at least one of the table, thereport and the graph.
 3. The method of claim 1, wherein the table iscreated by linking the sealed triangulated mesh and each respectivereserve estimate using the predefined identification properties.
 4. Themethod of claim 3, wherein the table is a tree table.
 5. The method ofclaim 4, wherein the report is created by processing the tree table withan extensible style-sheet language.
 6. The method of claim 5, whereinthe report includes a project summary, units information, a gross rockvolume value, compartment sources, sliced volume and area values.
 7. Themethod of claim 5, wherein the report includes a hierarchy of reserveestimates based on multiple scenarios.
 8. The method of claim 4, whereinthe graph is created using predefined parameters and the tree table. 9.A non-transitory program carrier device tangibly carryingcomputer-executable instructions for determining reserve estimates for areservoir, the instructions being executable to implement: loading asealed triangulated mesh, which includes a volume; creating a thicknessgrid using the sealed triangulated mesh; determining reserve estimatesin a reservoir model using one of the volume of the sealed triangulatedmesh and the thickness grid; converting the reserve estimates, thesealed triangulated mesh and the thickness grid into a printable string;storing the printable string in Processing History fields with a link toa 3D modeling engine and predefined identification properties describingthe reserve estimates; and generating at least one of a table, a reportand a graph for the reserve estimates and the predefined identificationproperties using the printable string.
 10. The program carrier device ofclaim 9, further comprising displaying the sealed triangulated mesh andthe thickness grid with the at least one of the table, the report andthe graph.
 11. The program carrier device of claim 9, wherein the tableis created by linking the sealed triangulated mesh and each respectivereserve estimate using the predefined identification properties.
 12. Theprogram carrier device of claim 11, wherein the table is a tree table.13. The program carrier device of claim 12, wherein the report iscreated by processing the tree table with an extensible style-sheetlanguage.
 14. The program carrier device of claim 13, wherein the reportincludes a project summary, units information, a gross rock volumevalue, compartment sources, sliced volume and area values.
 15. Theprogram carrier device of claim 13, wherein the report includes ahierarchy of reserve estimates based on multiple scenarios.
 16. Theprogram carrier device of claim 12, wherein the graph is created usingpredefined parameters and the tree table.
 17. A non-transitory programcarrier device tangibly carrying computer-executable instructions fordetermining reserve estimates for a reservoir, the instructions beingexecutable to implement: loading a sealed triangulated mesh, whichincludes a volume; creating a thickness grid using the sealedtriangulated mesh; determining reserve estimates in a reservoir modelusing one of the volume of the sealed triangulated mesh and thethickness grid; converting the reserve estimates, the sealedtriangulated mesh and the thickness grid into a printable string;storing the printable string with a link to a 3D modeling engine andpredefined identification properties describing the reserve estimates;generating at least one of a table, a report and a graph for the reserveestimates and the predefined identification properties using theprintable string; and displaying the sealed triangulated mesh and thethickness grid with the at least one of the table, the report and thegraph.
 18. The program carrier device of claim 17, wherein the table iscreated by linking the sealed triangulated mesh and each respectivereserve estimate using the predefined identification properties.
 19. Theprogram carrier device of claim 18, wherein the table is a tree table.20. The program carrier device of claim 19, wherein the report iscreated by processing the tree table with an extensible style-sheetlanguage.